Average household debt in America has tripled in the past 30 years. Much of this burden is unequally borne by racial/ethnic minorities and those with lower incomes, who face discrimination in obtaining loans and must devote more household resources to paying off debts. Being indebted is a strong predictor of suicide, depression, and other adverse mental health outcomes. However, its impact on physical health is underexplored. The overarching aim of this project is to elucidate debt as a socioeconomic determinant of health, with emphasis on elucidating mechanisms of embodiment and pinpointing specific categories of risk and disparity. We take a mixed-methods approach, utilizing primary and secondary data sources and a layered study design that incorporates epidemiologic, qualitative, and mechanistic approaches, to provide both breadth and depth in our investigation. Findings from this study are intended to shed light on the nature and patterns of debt's impact on health and lay groundwork for the development of targeted future intervention strategies. We capitalize on the diverse, yet complementary, expertise of our multidisciplinary team to create an integrated mixed-methods research program that blends statistical innovations with in-depth qualitative analysis and biological markers of debt-related disease risk. Specific aims are: 1) Use national, longitudinal data from the Panel Study of Income Dynamics (PSID) to document the association of basic dimensions of debt (absolute debt, debt-to-income ratio, secured and unsecured debt) with health and social disparities in health over time. Specifically, we will use marginal structural models to account for complex time-varying factors, and will test whether debt mediates key health inequalities and whether race/ethnicity or SES moderate associations of debt with health. 2) Conduct a qualitative study to elaborate salient dimensions of debt in greater depth and examine their role as psychosocial stressors. We will qualitatively elaborate salient dimensions of debt among diverse adults in Chicago and use structured ethnographic methods to clarify the structure of those dimensions. Findings will inform interpretation of quantitative analyses and guide measurement of debt exposure in Aim 3. 3) Conduct an intensive community-based biomarker study to examine the associations of debt dimensions with key stress biomarkers that are indicators of disease susceptibility. We will identify the type of debt exposure that are most predictive of stress-related disease biomarkers and health in a diverse community sample and test whether subjective stress mediates associations between debt and health outcomes. 4) Synthesize all three studies with an integrated mixed methods approach. In addition to drawing on qualitative findings to inform other aspects of the study, refine the biomarker study approach based on insights from initial PSID findings and synthesize data from all three studies to identify debt-related disease risk profiles.